Enclosure system with charging assembly

Abstract

The enclosure system includes a plurality of walls forming an interior volume. The enclosure system is configured to couple to a front end equipment module (EFEM) of a substrate processing system. The enclosure system further includes a charging assembly including a first charging coil. The enclosure system further includes one or more first support structures disposed within the interior volume below the first charging coil. The one or more first support structures are configured to support a first verification wafer within a threshold distance of the first charging coil and charge the first verification wafer via the charging assembly.

Description

[Technical Field]

[0001] Embodiments of the present disclosure relate to enclosure systems for use in connection with substrate processing systems, and more particularly to enclosure systems with charging assemblies.

[0002] Substrate processing and other electronic processing often employ platforms that use robotic arms to transport objects (e.g., substrates) between processing chambers, from storage areas (e.g., Front Opening Unified Pods (FOUPs)) to processing chambers, from processing chambers to storage areas, etc.

[0003] The following is a simplified summary of the disclosure in order to provide a basic understanding of some aspects of the disclosure. This summary is not an extensive overview of the disclosure. It is not intended to identify key or critical elements of the disclosure, nor is it intended to delineate the scope or claims of particular implementations of the disclosure. Its sole purpose is to present some concepts of the disclosure in a simplified form as a prelude to the more detailed description that is presented later.

[0004] In one aspect of the present disclosure, an enclosure system includes a plurality of walls forming an interior volume. The enclosure system is configured to couple to a front-end equipment module (EFEM) of a substrate processing system. The enclosure system further includes a charging assembly including a first charging coil. The enclosure system further includes one or more first support structures disposed within the interior volume below the first charging coil. The one or more first support structures are configured to support a first verification wafer within a threshold distance of the first charging coil and charge the first verification wafer via the charging assembly.

[0005] In another aspect of the present disclosure, a charging assembly of an enclosure system configured to couple to an EFEM of a substrate processing system includes a first charging coil disposed within an interior volume of the enclosure system above one or more first support structures that support a first verification wafer within a threshold distance of the first charging coil. The first verification wafer is positioned by the one or more first support structures to align a first charging interface of the first verification wafer with the first charging coil. The charging assembly further includes a rechargeable battery configured to charge the first verification wafer via the first charging coil. The rechargeable battery is configured to be recharged while coupled to the enclosure system.

[0006] In another aspect of the disclosure, a method includes receiving a first subset of sensor data from a validation wafer configured to be transferred by a robot of an EFEM of a substrate processing system from one or more support structures disposed within an interior volume formed by an enclosure system. The first subset is associated with at least one charge state of an electrical storage device of the validation wafer. Further, the method includes receiving a second subset of sensor data from a charging assembly of the enclosure system. The charging assembly is configured to charge the validation wafer in response to the validation wafer being placed on the one or more support structures. Further, the method includes performing a corrective action associated with the substrate processing system based on the sensor data. [Brief explanation of the drawings]

[0007] The present disclosure is illustrated by way of example, and not limitation, in the figures of the accompanying drawings, in which like reference numerals indicate similar elements. It should be noted that different references to "an embodiment" or "an embodiment" in this disclosure do not necessarily refer to the same embodiment, but that such references do refer to at least one. [Figure 1A] 1 illustrates a processing system in accordance with certain embodiments. [Figure 1B] FIG. 1 is a block diagram illustrating an exemplary system architecture in accordance with certain embodiments. [Figure 2A] ~ [Figure 2B] FIG. 1 illustrates a front view of an enclosure system in accordance with certain embodiments. [Figure 2C] 1 illustrates a cross-sectional top view of an enclosure system in accordance with certain embodiments. [Figure 2D] 1 illustrates a top view of an enclosure system in accordance with certain embodiments. [Figure 3] 1 illustrates a schematic diagram of a charging assembly of an enclosure system, according to certain embodiments. [Figure 4] 1 illustrates a side view of a charging assembly of an enclosure system, according to certain embodiments. [Figure 5] 1 illustrates a flow diagram of a method for causing corrective action to be taken, according to certain embodiments. [Figure 6A] ~ [Figure 6C] 1 illustrates a flow diagram of a method relating to a machine learning model, according to certain embodiments. [Figure 7] FIG. 1 is a block diagram illustrating a computer system in accordance with certain embodiments. Detailed Description of the Embodiments

[0008] SUMMARY OF THE INVENTION The embodiments described herein relate to an enclosure system that includes a charging assembly (eg, a FOUP for verification wafer charging and host communication, etc.).

[0009] A substrate processing system is used to process substrates. The substrate processing system includes a factory interface (also called an Equipment Front End Module (EFEM)), a load lock, a transfer chamber, and a processing chamber. A substrate storage system (e.g., a FOUP) is coupled to the factory interface (e.g., docked via a load port), a factory interface robot transfers substrates from the substrate storage system (e.g., via the factory interface) to the load lock, and a transfer chamber robot transfers substrates from the load lock (e.g., via the transfer chamber) to a processing chamber for processing. The processed substrate is then transferred to the load lock by the transfer chamber robot and from the load lock to the substrate storage system by the factory interface robot. The factory interface maintains a first environment (e.g., atmospheric environment, inert environment, etc.), and the transfer chamber maintains a second environment (e.g., vacuum environment, etc.) to avoid contamination of the substrate and the substrate processing system.

[0010] Components of a substrate processing system wear over time and need to be removed and replaced, for example, a process kit ring located within a processing chamber and wears over time due to substrate processing operations and needs to be replaced.

[0011] Conventionally, substrate processing systems (e.g., transfer chambers, processing chambers, etc.) are opened to inspect the substrate processing system or replace components (e.g., process kit rings, etc.), which contaminates the substrate processing system and keeps the substrate processing system offline through the recommissioning process, reducing yield, consuming energy, and wasting operator time.

[0012] The devices, systems, and methods disclosed herein provide an enclosure system that solves the problems of conventional systems. The enclosure system may be a FOUP configured to store and transport objects such as carriers, process kit rings, substrates, and validation wafers. Each carrier can support one or more process kit rings. Additionally, the enclosure system can be configured to charge validation wafers and receive sensor data from validation wafers.

[0013] The enclosure system includes walls that form an interior volume. The walls can include side walls, a bottom wall, a top wall, and / or an enclosure door. The enclosure system (e.g., via one or more walls, etc.) is configured to couple to an EFEM (e.g., by placing the enclosure system on a load port, etc.). In some embodiments, the top wall of the enclosure system is an enclosure lid that is removably attached to the one or more side walls and at least partially encloses the interior volume of the enclosure system. In some embodiments, the enclosure door of the enclosure system is removably attached to the one or more side walls. In some embodiments, the enclosure system (e.g., enclosure door, walls, enclosure lid, etc.) provides a sealed environment to the interior volume of the enclosure system.

[0014] In some embodiments, a verification wafer is stored within the interior volume of the enclosure system. The verification wafer includes one or more sensors (e.g., an image sensor, a pressure sensor, a temperature sensor, etc.). The verification wafer is transferred from the enclosure system to one or more other parts of the substrate processing system to provide sensor data related to the substrate processing system. In some embodiments, the verification wafer is transferred to a processing chamber to collect image data and / or other data to determine if a process kit ring needs to be replaced.

[0015] In some embodiments, the enclosure system includes a charging assembly configured to charge a verification wafer disposed within the enclosure system. In some embodiments, the charging system includes a charging coil. The charging coil can be configured to charge the verification wafer via inductive charging.

[0016] In some embodiments, the enclosure system includes one or more support structures disposed within the interior volume to support one or more objects (e.g., a carrier, a verification wafer, a process kit ring, etc.) within the enclosure system. One or more first support structures are disposed below the charging coil and configured to support the verification wafer within the interior volume of the enclosure system for charging the verification wafer via the charging assembly. In some embodiments, the one or more first support structures are configured to support the verification wafer within a threshold distance of the charging coil for charging the verification wafer (e.g., via inductive charging, etc.) via the charging assembly. In some embodiments, the one or more first support structures are configured to position the verification wafer to align a charging interface of the verification wafer with the charging coil.

[0017] In some embodiments, sensor data is received from the verification wafer and / or the enclosure system, and corrective action is performed based on the sensor data. For example, in response to receiving sensor data (e.g., images, etc.) associated with a process kit ring in a processing chamber, corrective action can be performed to replace the process kit ring with a new process kit ring from the enclosure system.

[0018] The devices, systems, and methods disclosed herein offer advantages over conventional solutions. The present disclosure provides a verification wafer for testing components (e.g., process chambers, etc.) of a substrate processing system and provides sensor data related to the components without opening the sealed environment (e.g., without opening the transfer chamber, without opening the process chamber, etc.), compared to conventional systems in which a sealed environment is opened to test the components. This allows the present disclosure to achieve higher yields, reduced energy usage, less contamination, and less operator time, compared to conventional systems. The disclosed enclosure system also allows the verification wafer and / or sensor data to be transmitted from the enclosure system without opening the enclosure system or removing the verification wafer from the enclosure system, compared to conventional systems in which a substrate processing system is opened for testing. This allows the present disclosure to reduce contamination of the enclosure system and avoid lengthy decontamination processes. The disclosed enclosure system also allows the verification wafer to be charged without opening the enclosure system or removing the verification wafer from the enclosure system. Additionally, the disclosed enclosure system allows for replacement of components of a substrate processing system (e.g., a process kit ring, etc.) without opening the sealed environment and without the time- and energy-intensive recommissioning process of conventional systems. The disclosed enclosure system allows for maintenance operations (e.g., replacing a process kit ring in a processing chamber, etc.) to be performed without human intervention after inspection (e.g., with a verification wafer, etc.), making maintenance of the processing chamber more efficient compared to conventional systems.

[0019] Although portions of this disclosure refer to process kit rings and carriers and verification wafers, this disclosure may be applied to different types of contents (e.g., other components of a substrate processing system, etc.). Although portions of this disclosure refer to substrate processing systems, this disclosure may be applied to other types of systems (e.g., other manufacturing systems, etc.). Although portions of this disclosure refer to the enclosure system being a FOUP, the enclosure system of this disclosure may be a side storage pod (SSP) or other types of enclosures (e.g., other enclosures of a substrate processing system, etc.).

[0020] FIG. 1A illustrates a processing system 100A (e.g., a substrate processing system, a wafer processing system, a semiconductor processing system, etc.) in accordance with certain embodiments. The processing system 100A includes a factory interface 101 (also referred to as an EFEM) and load ports 129 (e.g., load ports 129A-D, etc.). In some embodiments, the load ports 129A-D are directly attached (e.g., sealed, etc.) to the factory interface 101. An enclosure system 130 (e.g., a cassette, FOUP, process kit enclosure system, etc.) is configured to removably couple (e.g., dock, etc.) to the load ports 129A-D. Referring to FIG. 1A, enclosure system 130A is coupled to load port 129A, enclosure system 130B is coupled to load port 129B, enclosure system 130C is coupled to load port 129C, and enclosure system 130D is coupled to load port 129D. In some embodiments, one or more enclosure systems 130 are coupled to the load ports 129 to move substrates and / or other substrates into and out of the processing system 100A. Each enclosure system 130 seals to its respective load port 129. In some embodiments, a first enclosure system 130A is docked to the load port 129A (e.g., to replace a used process kit ring and / or to charge and / or store a verification wafer, etc.). Once such an operation is performed, the first enclosure system 130A is undocked from the load port 129A, and a second enclosure system 130 (e.g., a FOUP containing substrates, etc.) is docked to the same load port 129A. In some embodiments, the first enclosure system 130A is semi-permanently docked to the load port 129A. In certain embodiments, the first enclosure system 130A is integrated with the factory interface 101. In some embodiments, enclosure system 130 (eg, enclosure system 130A, etc.) is an enclosure system that includes support structures for aligning a carrier, a process kit ring, and / or a verification wafer.

[0021] In some embodiments, the load port 129 includes a front interface that forms a vertical opening (or a substantially vertical opening). Additionally, the load port 129 includes a horizontal surface for supporting an enclosure system 130 (e.g., a cassette, a process kit enclosure system, etc.). Each enclosure system 130 (e.g., a substrate FOUP, a process kit enclosure system, etc.) has a front interface that forms a vertical opening. The front interface of the enclosure system 130 is sized to interface (e.g., seal, etc.) with the front interface of the load port 129 (e.g., the vertical opening of the enclosure system 130 is approximately the same size as the vertical opening of the load port 129, etc.). The enclosure system 130 is positioned on the horizontal surface of the load port 129, and the vertical opening of the enclosure system 130 is aligned with the vertical opening of the load port 129. The front interface of the enclosure system 130 is interconnected (e.g., clamped, fastened, sealed, etc.) with the front interface of the load port 129. The bottom plate (e.g., base plate, etc.) of the enclosure system 130 has features that engage with the horizontal surfaces of the load port 129 (e.g., load features such as recesses or receptacles that engage with kinematic pin features of the load port, load port features for pin clearance, and / or enclosure system docking tray latch clamp features, etc.). The same load port 129 can be used for different types of enclosure systems 130 (e.g., process kit enclosure systems, cassettes containing substrates, etc.).

[0022] In some embodiments, enclosure system 130 includes one or more shelves for aligning carriers, process kit rings, and / or validation wafers. In some embodiments, enclosure system 130 includes one pair of shelves for aligning carriers and / or contents disposed on the carriers (e.g., process kit rings, processing chamber components, validation wafers, etc.). In some embodiments, enclosure system 130 includes two pairs of shelves, three pairs of shelves, four pairs of shelves, five pairs of shelves, six pairs of shelves, seven pairs of shelves, eight pairs of shelves, etc. for aligning objects (e.g., carriers, process kit rings, validation wafers, etc.).

[0023] In some embodiments, the enclosure system 130 (e.g., a process kit enclosure system, etc.) contains one or more content items 113 (e.g., one or more of a process kit ring, an empty process kit ring carrier, a process kit ring disposed on a process kit ring carrier, a validation wafer, etc.). In some examples, the enclosure system 130 is coupled to the factory interface 101 (e.g., via a load port 129, etc.) and can automatically transfer a process kit ring on a process kit ring carrier to the processing system 100A to replace a used process kit ring. In some examples, the enclosure system 130 is coupled to the factory interface 101 and can automatically transfer a validation wafer to the processing system 100A to inspect the processing chamber 107 or one or more components of the processing chamber.

[0024] In some embodiments, the enclosure system 130 includes a charging assembly for charging one or more verification wafers. The enclosure system 130 may include a battery for storing electricity received from an external source. In some embodiments, the enclosure system 130 includes electrical connections for connecting to and receiving electricity from components of the processing system 100A via electrical connections of the components (e.g., factory interface 101, load port 129, etc.) of the processing system 100A. In some embodiments, the enclosure system 130 includes communication connections (e.g., electrical communication connections) for transmitting data to and receiving data from the components (e.g., factory interface 101, load port 129, etc.) of the processing system 100A via communication connections of the components (e.g., factory interface 101, load port 129, etc.). In some embodiments, the charging system includes a first coil for charging the verification wafer via inductive charging. Additionally, in some embodiments, the enclosure system 130 includes a processing device (e.g., processor, client device, computing device, etc.) for receiving data from the verification wafer, the factory interface 101, a client device, a server device, the controller 109, etc. The received data may indicate the status of the verification wafer and / or the status of the processing chamber components. The processor of the enclosure system 130 may be in communication with the controller 109.

[0025] Additionally, in some embodiments, the processing system 100A includes first vacuum ports 103a, 103b coupling the factory interface 101 to each degassing chamber 104a, 104b (e.g., load locks, etc.). Second vacuum ports 105a, 105b are coupled to each degassing chamber 104a, 104b and are disposed between the degassing chambers 104a, 104b and the transfer chamber 106 to allow transfer of substrates and contents 113 (e.g., process kit rings, validation wafers, etc.) to the transfer chamber 106. In some embodiments, the processing system 100A includes and / or uses one or more degassing chambers 104 and a corresponding number of vacuum ports 103, 105 (e.g., the processing system 100A includes a single degassing chamber 104, a single first vacuum port 103, and a single second vacuum port 105, etc.). The transfer chamber 106 includes a plurality of processing chambers 107 (e.g., four processing chambers 107, six processing chambers 107, etc.) arranged around and coupled to the transfer chamber 106. The processing chambers 107 are coupled to the transfer chamber 106 through respective ports 108, such as slit valves. In some embodiments, the factory interface 101 is at high pressure (e.g., atmospheric pressure, etc.) and the transfer chamber 106 is at low pressure (e.g., vacuum, etc.). Each degassing chamber 104 (e.g., load lock, pressure chamber, etc.) has a first door (e.g., first vacuum port 103, etc.) that seals the degassing chamber 104 from the factory interface 101 and a second door (e.g., second vacuum port 105, etc.) that seals the degassing chamber 104 from the transfer chamber 106. While the first door is open and the second door is closed, the contents are transferred from the factory interface 101 to the degassing chamber 104, the first door is closed, the pressure in the degassing chamber 104 is reduced to match the transfer chamber 106, the second door is opened, and the contents are transferred from the degassing chamber 104. A local center finding (LCF) device is used to align the contents in the transfer chamber 106 (e.g., before entering the processing chamber 107, after exiting the processing chamber 107, etc.).

[0026] In some embodiments, the processing chamber 107 includes an etch chamber, a deposition chamber (including atomic layer deposition, chemical vapor deposition, physical vapor deposition, or plasma-enhanced versions thereof), an anneal chamber, or the like.

[0027] The factory interface 101 includes a factory interface robot 111. The factory interface robot 111 includes a robot arm, such as a Selective Compliance Assembly Robot Arm (SCARA) robot. Examples of SCARA robots include a two-link SCARA robot, a three-link SCARA robot, a four-link SCARA robot, etc. The factory interface robot 111 includes an end effector at the end of the robot arm. The end effector is configured to pick up and handle specific objects, such as substrates. Alternatively or additionally, the end effector is configured to handle objects, such as carriers, process kit rings (e.g., edge rings, etc.), and / or verification wafers. The robot arm has one or more links or members (e.g., wrist members, upper arm members, forearm members, etc.) configured to move to move the end effector in various directions and to various locations.

[0028] The factory interface robot 111 is configured to transport objects between the enclosure system 130 (e.g., cassettes, FOUPs, etc.) and the degassing chambers 104a, 104b (or load locks). While conventional systems involve misalignment of content and opening (e.g., disassembly, breaking seals, contamination, etc.) the processing system 100A (e.g., factory interface 101, etc.) to align misaligned content, the processing system 100A is configured to facilitate alignment of content (e.g., via one or more support structures of the enclosure system 130, via a removable rear window of the enclosure system 130, etc.) without an operator having to open (e.g., disassembly, breaking seals, contamination, etc.) the processing system 100A. Thus, in some embodiments, a sealed environment including the interior volumes of the enclosure system 130 and the factory interface 101 is maintained during alignment of content (e.g., via one or more support structures of the enclosure system 130, via a removable rear window of the enclosure system 130, etc.).

[0029] The transfer chamber 106 includes a transfer chamber robot 115. The transfer chamber robot 115 includes a robot arm with an end effector at the end. The end effector is configured to handle a particular object, such as a substrate. In some embodiments, the transfer chamber robot 115 is a SCARA robot, but in some embodiments, it has fewer links and fewer degrees of freedom than the factory interface robot 111.

[0030] The controller 109 controls various aspects of the processing system 100A. In some embodiments, the controller 109 controls only the processing system 100A (e.g., does not control other processing systems). In some embodiments, the controller 109 controls multiple processing systems. In some embodiments, the controller controls substrate processing equipment. The controller 109 is and / or includes a computing device, such as a personal computer, a server computer, a programmable logic controller (PLC), a microcontroller, etc. The controller 109 includes one or more processing devices. In some embodiments, these processing devices are general-purpose processing devices, such as a microprocessor, a central processing unit, etc. More specifically, in some embodiments, the processing devices are complex instruction set computing (CISC) microprocessors, reduced instruction set computing (RISC) microprocessors, very long instruction word (VLIW) microprocessors, or processors that execute other instruction sets or combinations of instruction sets. In some embodiments, the processing devices are one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), a network processor, etc. In some embodiments, the controller 109 includes data storage (e.g., one or more disk drives and / or solid state drives, etc.), main memory, static memory, network interfaces, and / or other components. In some embodiments, the controller 109 executes instructions to perform any one or more of the methods or processes described herein. The instructions are stored on a computer-readable storage medium, which may include one or more of main memory, static memory, secondary storage, and / or a processing device (during execution of the instructions). In some embodiments, the controller 109 receives signals from and sends controls to the factory interface robot 111 and the substrate transfer chamber robot 115.

[0031] FIG. 1A schematically illustrates the transfer of contents 113 (e.g., process kit rings, validation wafers, etc., disposed on a carrier) to a processing chamber 107. According to one aspect of the present disclosure, the contents 113 are removed from the enclosure system 130 via a factory interface robot 111 disposed within the factory interface 101. The factory interface robot 111 transfers the contents 113 to each of the degassing chambers 104a, 104b via one of the first vacuum ports 103A, 103B. A transfer chamber robot 115 disposed within the transfer chamber 106 removes the contents 113 from either of the degassing chambers 104a, 104b via a second vacuum port 105a or 105b. The transfer chamber robot 115 moves the contents 113 to the transfer chamber 106, where the contents 113 are transferred to the processing chambers 107 via respective ports 108. Although not shown in FIG. 1A for clarity, the transport of contents 113 may include transport of process kit rings arranged on carriers, transport of empty process kit ring carriers, transport of verification wafers, transport of components of processing system 100A arranged on carriers, transport of substrates arranged on carriers, transport of empty carriers, transport of process kit rings without carriers, etc.

[0032] 1A illustrates one example of the transfer of contents 113, but other examples are contemplated. In some examples, the enclosure system 130 may be coupled to the transfer chamber 106 (e.g., via a load port attached to the transfer chamber 106). From the transfer chamber 106, the contents 113 are loaded into the processing chamber 107 by the transfer chamber robot 115. The processed contents 113 (e.g., used process kit rings, validation wafers, etc.) are removed from the processing system 100A in the reverse manner of that described herein.

[0033] In some embodiments, the enclosure system disclosed herein is a FOUP (e.g., docked to a load port in communication with a factory interface, etc.). In some embodiments, the enclosure system disclosed herein is a side storage pod (SSP) that is attached directly to the factory interface 101. In some embodiments, an additional SSP is positioned in communication with the factory interface 101 opposite the depicted SSP. In some embodiments, the processed contents 113 are removed from the degassing chamber 104 and loaded into the SSP via the robot 111 (e.g., for cooling, etc.). In some embodiments, the processed contents 113 are removed from the degassing chamber 104 and loaded into the SSP via the robot 111 (e.g., for cooling, etc.). In some embodiments, a validation wafer can be removed from the SSP and placed into the SSP via the robot 111.

[0034] When multiple enclosure systems 130 or a combination of enclosure systems 130 and SSPs are used, in some embodiments, one SSP or enclosure system 130 is used for unprocessed contents 113 (e.g., new process kit rings, charged validation wafers, etc.) and another SSP or enclosure system 130 is used to receive processed contents 113 (used process kit rings, used validation wafers, etc.). The enclosure system 130 is used to align the contents 113 (e.g., via one or more support structures within the enclosure system 130, via a removable rear window of the enclosure system 130, etc.) before the contents 113 are transferred by the robotic arm and / or before the enclosure system 130 is transferred. Aligning the content 113 through one or more support structures that align the content 113 and / or a removable rear window of the enclosure system 130 allows the robotic arm to correctly remove the content 113 from a specific location within the enclosure system 130, allows the content 113 to be properly secured within the enclosure system 130 (e.g., one or more support structures secure the content 113), and allows the enclosure system 130 to properly transport the content 113.

[0035] The processing system 100A includes a chamber, such as a factory interface 101 (e.g., a front-end equipment module (EFEM)), and adjacent chambers adjacent to the factory interface 101 (e.g., a load port 129, an enclosure system 130, a degassing chamber 104 of an SSP, a load lock, etc.). One or more chambers are sealed (e.g., each chamber is sealed, etc.). The adjacent chambers are sealed to the factory interface 101. In some embodiments, one or more chambers (e.g., the factory interface 101 and / or adjacent chambers, etc.) are supplied with an inert gas (e.g., one or more of nitrogen, argon, neon, helium, krypton, or xenon, etc.) to provide one or more inert environments. In some examples, the factory interface 101 is an inert EFEM, maintaining an inert environment (e.g., an inert EFEM mini-environment, etc.) within the factory interface 101, thereby eliminating the need for a user to enter the factory interface 101 (e.g., the processing system 100A is configured to prevent manual access within the factory interface 101, etc.).

[0036] In some embodiments, a gas flow (e.g., an inert gas, nitrogen, etc.) is provided to one or more chambers (e.g., factory interface 101, enclosure system 130, etc.) of processing system 100A. In some embodiments, the gas flow is greater than leakage through one or more chambers to maintain a positive pressure in the one or more chambers. In some embodiments, the inert gas in factory interface 101 is recirculated. In some embodiments, a portion of the inert gas is exhausted. In some embodiments, the gas flow rate of non-recirculated gas into factory interface 101 is greater than the exhaust gas flow rate and gas leakage to maintain a positive inert gas pressure in factory interface 101. In some embodiments, factory interface 101 is coupled to one or more valves and / or pumps to provide gas flow into and out of factory interface 101. A processing device (e.g., of controller 109) controls the gas flow rate into and out of factory interface 101 and / or enclosure system 130. In some embodiments, the processing device receives sensor data from one or more sensors (e.g., oxygen sensors, humidity sensors, motion sensors, door operation sensors, temperature sensors, pressure sensors, etc.) and determines the flow rate of inert gas into and out of the factory interface 101 and / or enclosure system 130 based on the sensor data.

[0037] The enclosure system 130 can align the contents 113 (e.g., carriers, process kit rings, validation wafers, etc.) without opening the sealed environment in the factory interface 101 and adjacent chambers. When the enclosure system 130 is docked to the load port 129, it is sealed to the load port 129. The enclosure system 130 provides purge port access, which allows the interior of the enclosure system 130 to be purged before opening the enclosure system 130, minimizing disturbance of the inert environment in the factory interface 101.

[0038] 1B is a block diagram illustrating an exemplary system architecture according to aspects of the present disclosure. In some embodiments, computer system architecture 100B can be included as part of a manufacturing system (e.g., processing system 100A, etc.) for processing substrates. Computer system architecture 100B includes client device 120, controller 109 (e.g., a facility controller, a controller of processing system 100A, etc.), manufacturing equipment 124 (e.g., processing system 100A), sensors 126, verification wafers 128, prediction server 112 (e.g., for generating prediction data, etc.), enclosure system 130 (e.g., FOUP, SSP, etc.), and data store 140. Prediction server 112 can be part of prediction system 110. Furthermore, prediction system 110 can include server machines 170 and 180.

[0039] Client device 120, controller 109, manufacturing equipment 124, prediction server 112, data store 140, prediction server 112, server machine 170, and server machine 180 can each be hosted by one or more computing devices, including a server computer, a desktop computer, a laptop computer, a tablet computer, a notebook computer, a personal digital assistant (PDA), a mobile communication device, a mobile phone, a handheld computer, a cloud server, a cloud-based system (e.g., a cloud service device, a cloud network device, etc.), or a similar computing device.

[0040] The sensors 126 are configured to acquire sensor data 141 before, during, or after substrate processing by the fabrication tool 124. In some embodiments, one or more sensors 126 are disposed within the fabrication tool 124. In some embodiments, the verification wafer 128 is a test wafer that includes sensors 126 (e.g., image sensors such as cameras) that provide sensor data 141 for inspecting the interior of a chamber of the fabrication tool 124 and / or components of the fabrication tool 124.

[0041] The sensor data 141 may include one or more of temperature data (e.g., heater temperature, etc.), clearance data (SP), pressure data, high frequency radio frequency (HFRF) data, electrostatic chuck (ESC) voltage data, current data, flow data, power data, voltage data, light frequency data, waveform data, image data, etc. The sensor data 141 may be associated with or indicative of a manufacturing parameter, such as a hardware parameter, such as a setting or component (e.g., size, type, etc.) of the manufacturing tool 124, or a process parameter of the manufacturing tool 124. In some embodiments, the sensor data 141 may be provided while the manufacturing tool 124 is performing a manufacturing process (e.g., equipment readings during product processing), or in additional or alternative embodiments, after the manufacturing tool 124 has completed a manufacturing process. The sensor data 141 may be associated with or indicative of the quality of a component (e.g., a process kit ring, etc.).

[0042] The verification wafer 128 provides data related to the chambers and / or components of the manufacturing tool 124. In some embodiments, the verification wafer 128 collects data using one or more sensors (e.g., imaging devices such as cameras). The verification wafer 128 can include multiple image sensors for capturing images of the lid of a chamber (e.g., a process chamber, EFEM, transfer chamber, load lock, FOUP, SSP, etc.), one or more side walls of the chamber, a bottom wall of the chamber, and / or components of the chamber (e.g., a process kit ring, etc.). Images from multiple image sensors can be stitched together to generate a stitched image of the entire interior surface of the chamber. In some embodiments, the image sensors capture light in the visible spectrum. In some embodiments, the image sensors capture thermal radiation and / or visible light.

[0043] In some embodiments, the verification wafer 128 includes one or more sensors (e.g., three sensors) that emit and receive a beam of light and measure the distance traveled by the beam of light. In some embodiments, the verification wafer 128 includes a displacement sensor, an impedance sensor, and / or an acoustic sensor. The verification wafer 128 can include multiple sensors including a pressure sensor, a temperature sensor, a vibration sensor, an accelerometer, and / or a reflectometry sensor. In some embodiments, the verification wafer 128 includes a piezoresistive sensor and / or a piezoelectric acoustic sensor. In some embodiments, the verification wafer 128 includes a non-contact sensor. The non-contact sensor can include a radar sensor capable of scanning the surface of a component of the processing chamber. Further, the non-contact sensor can include an X-ray emitter (e.g., an X-ray laser, etc.) and an X-ray detector. Furthermore, the verification wafer 128 can include an illumination component. The illumination component can at least partially illuminate the interior volume of the chamber.

[0044] In some embodiments, the verification wafer 128 provides sensor data 141 for determining whether components of the manufacturing tool 124 are in a predetermined state (e.g., a predetermined orientation, etc.). For example, the verification wafer 128 can provide sensor data 141 for verifying the placement of a process kit ring in a processing chamber of the manufacturing tool 124. The sensor data 141 can include alignment data (e.g., of the process kit ring positioned in the processing chamber), image data (e.g., one or more captured images, etc.), light beam data (e.g., laser light beam data, etc.), vibration data, temperature data, humidity data, process gas data, particle data, pressure data, proximity data, displacement data, impedance data, acoustic data, placement data, etc. The sensor data 141 can be associated with the state of the process kit ring positioned in the processing chamber. In some embodiments, the sensor data 141 can be associated with the state of the verification wafer 128.

[0045] The verification wafer 128 may include memory for storing sensor data. The verification wafer 128 may include a power source (e.g., an electrical storage device, a rechargeable battery, etc.). In some embodiments, the verification wafer 128 includes one or more supercapacitors that store electrical energy used to power the verification wafer 128. The supercapacitors may be high-capacity capacitors with capacitance values ​​much higher than conventional capacitors. In some embodiments, the supercapacitors store 10 to 100 times more electrical energy per unit volume than electrolytic capacitors. In some embodiments, the supercapacitors are rechargeable. If the supercapacitors are dropped and damaged within a processing chamber, they may not contaminate the processing chamber. In some embodiments, the supercapacitors may provide high current for short periods of time. Furthermore, the supercapacitors may not pose a fire hazard if dropped onto a hot chuck of a processing chamber.

[0046] The validation wafer 128 can be charged by a charging assembly of the enclosure system 130 (e.g., a FOUP, an SSP, etc.). The validation wafer 128 provides sensor data 141, and the corrective action component 123 can determine the status of the processing chamber and / or the status of the validation wafer 128 based on the sensor data 141. For example, the validation wafer 128 can provide sensor data 141 (e.g., image data, etc.), and the corrective action component 123 can determine whether to perform corrective action to replace a process kit ring based on the sensor data 141. The validation wafer 128 can include whitelisting and / or blacklisting functionality, which enables the validation wafer 128 to communicate data to the appropriate destination (e.g., the client device 120, the controller 121, the data store 140, the enclosure system 130, the manufacturing tool 124, etc.). For example, a whitelist may include a feature that allows only certain destination devices (e.g., a specific client device 120, a specific controller 121, a specific data store 140, a specific enclosure system 130, a specific manufacturing equipment 124, etc.) to communicate with a specific verification wafer 128. In some embodiments, under a whitelist scheme, only certain devices can receive data from a specific verification wafer 128. In another example, a blacklist may include a feature that prevents certain destination devices from communicating with a specific verification wafer 128. In some embodiments, under a blacklist scheme, certain devices can be prevented from receiving data from a specific verification wafer 128. The verification wafer 128 can communicate wirelessly with remote devices (e.g., a client device 120, a controller 121, a data store 140, an enclosure system 130, a manufacturing equipment 124, etc.). In some embodiments, the verification wafer 128 communicates via WiFi. In some embodiments, the verification wafer 128 communicates via Bluetooth. In some embodiments, the verification wafer 128 includes a wireless (e.g., Bluetooth, etc.) interface for communicating with a host device.In another example, the validation wafer 128 provides sensor data 141, and the corrective action component 123 determines whether to perform a corrective action to charge (e.g., electrically charge, etc.) the validation wafer 128 based on the sensor data 141. In some embodiments, the sensor data 141 provided by the validation wafer 128 can include image data (e.g., an image, etc.).

[0047] The client device 120 may include computing devices such as personal computers (PCs), laptops, mobile phones, smartphones, tablet computers, netbook computers, network-connected televisions ("smart TVs"), network-connected media players (e.g., Blu-ray players, etc.), set-top boxes, over-the-top (OTT) streaming devices, operator boxes, cloud servers, cloud-based systems (e.g., cloud service devices, cloud network devices), etc. The client device 120 may execute cloud-based operations (e.g., prediction system 110, data store 140, manufacturing equipment 124, enclosure system 130, verification wafer 128, controller 121, etc.). In some embodiments, sensor data 141 is received from the client device 120. In some embodiments, the client device 120 displays a graphical user interface (GUI) that allows a user to provide as input a portion of the manufacturing equipment 124 to inspect (e.g., a process kit ring, etc.). In some embodiments, the client device 120 includes a corrective action component 123 for executing one or more methods (see, e.g., FIG. 5).

[0048] The controller 109 may include one or more computing devices, such as a rack-mounted server, a router computer, a server computer, a personal computer, a mainframe computer, a laptop computer, a tablet computer, a desktop computer, a graphics processing unit (GPU), an accelerator application-specific integrated circuit (ASIC) (e.g., a Tensor Processing Unit (TPU)), a cloud server, one or more cloud-stored systems, etc. In some embodiments, the controller 109 includes a corrective action component 123 for executing one or more methods (see, e.g., FIG. 5 ). In some embodiments, the controller 109 controls manufacturing equipment 124. In some embodiments, the controller 109 controls a manufacturing facility that includes manufacturing equipment 124.

[0049] Data store 140 may be memory (e.g., random access memory, etc.), a drive (e.g., hard drive, flash drive, etc.), a database system, a cloud-based system, or another type of component or device capable of storing data. Data store 140 may include multiple storage components (e.g., multiple drives or multiple databases, etc.) that may span multiple computing devices (e.g., multiple server computers, multiple clouds, etc.).

[0050] The data store 140 can store sensor data 141 received from the sensors 126, the validation wafer 128, and / or the enclosure system 130. For example, the data store 140 can store sensor data 141 collected by the validation wafer 128 during testing of a process chamber. The sensor data 141 can include historical sensor data 142 (e.g., sensor data collected by the validation wafer 128 during historical testing, etc.) and / or current sensor data 143 (e.g., sensor data collected by the validation wafer 128 during a current testing, etc.). The historical sensor data 142 can be used to train the machine learning model 190. The current sensor data 143 can be used to determine predicted data 147 (e.g., using the trained machine learning model 190, etc.).

[0051] The data store 140 can store performance data 144. The performance data 144 can include historical performance data 145 and current performance data 146. In some embodiments, the corrective action component 123 generates the performance data 144 based on the sensor data 141. For example, the corrective action component 123 determines the performance data 144 indicating whether the process kit ring needs to be replaced (e.g., the process kit ring is defective) based on the sensor data 141 including image data of a process kit ring disposed in a processing chamber of the manufacturing tool 124. In another example, the corrective action component 123 determines the performance data 144 indicating whether the validation wafer 128 needs to be recharged (e.g., the charge level of the supercapacitor of the validation wafer 128 is low) based on the sensor data 141 including charge data of the validation wafer 128. In yet another example, the corrective action component 123 determines performance data 144 indicating whether the enclosure system charging assembly battery needs to be recharged (e.g., the enclosure system charging assembly battery is low, etc.) based on sensor data 141 including charge data for the enclosure system charging assembly battery. In some embodiments, the corrective action component 123 determines performance data 144 based on user input responsive to the sensor data 141 (e.g., the user examines image data and provides user input indicating that a process kit ring needs to be replaced, etc.).

[0052] The data store 140 can store predictive data 147. The predictive data 147 may be predicted performance data 144. The corrective action component 123 provides the sensor data 141 to the prediction component 114 and receives predictive data from the prediction component 114 indicating corrective actions that need to be taken. In some embodiments, the corrective action component 123 provides the sensor data 141 of image data associated with an installed process kit ring to the prediction component 114, and the prediction component 114 provides the predictive data 147 of whether the process kit ring needs to be replaced (e.g., a user does not need to inspect the sensor data 141).

[0053] In some embodiments, prediction system 110 includes server machine 170 and server machine 180. Server machine 170 includes training set generator 172 that can generate training datasets (e.g., a set of data inputs and a set of target outputs) for training, validating, and / or testing machine learning model 190. Some operations of training set generator 172 are described in more detail below with reference to FIG. 6A . In some embodiments, training set generator 172 can divide training data into a training set, a validation set, and a test set. In some embodiments, prediction system 110 generates multiple training datasets.

[0054] Server machine 180 includes a training engine 182, a validation engine 184, a selection engine 186, and / or a test engine 188. An engine may refer to hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, a processing device, etc.), software (e.g., instructions executed on a processing device, a general-purpose computer system, or a dedicated machine, etc.), firmware, microcode, or a combination thereof. Training engine 182 may train a machine learning model 190. Machine learning model 190 may refer to a model product created by training engine 182 using training data including training inputs and corresponding target outputs (correct answers for each training input). Training engine 182 may find patterns in the training data that map training inputs to target outputs (predicted answers) and provide a machine learning model 190 that captures these patterns. In some embodiments, the machine learning model 190 uses one or more of a support vector machine (SVM), a radial basis function (RBF), clustering, supervised machine learning, semi-supervised machine learning, unsupervised machine learning, a k-nearest neighbor algorithm (k-NN), linear regression, supervised regression, random forests, neural networks (e.g., artificial neural networks, etc.), and the like.

[0055] The validation engine 184 may validate the trained machine learning models 190 using the corresponding feature sets of the validation set from the training set generator 172. The validation engine 184 may determine the accuracy of each of the trained machine learning models 190 based on the corresponding feature sets of the validation set. The validation engine 184 may discard trained machine learning models 190 having an accuracy that does not meet a threshold accuracy. In some embodiments, the selection engine 186 may select a trained machine learning model 190 having an accuracy that meets the threshold accuracy. In some embodiments, the selection engine 186 may select the trained machine learning model 190 with the highest accuracy among the trained machine learning models 190.

[0056] The test engine 188 may test the trained machine learning models 190 using the corresponding feature sets of the test set from the training set generator 172. For example, a first trained machine learning model 190 trained using a first feature set of the training set may be tested using a first feature set of the test set. The test engine 188 may determine the trained machine learning model 190 with the highest accuracy among all the trained machine learning models based on the test set.

[0057] The prediction server 112 includes a prediction component 114 that can provide sensor data 141 collected by one or more sensors 126 (e.g., sensor data 141 collected by a verification wafer 128 during inspection of a chamber of a manufacturing tool 124, such as the processing chamber 107 of FIG. 1A) to a trained machine learning model 190 and run the trained machine learning model 190 on the input to obtain one or more outputs.

[0058] Client device 120, controller 109, manufacturing equipment 124, sensor 126, validation wafer 128, enclosure system 130, prediction server 112, data store 140, server machine 170, and / or server machine 180 may be connected to one another via network 131. In some embodiments, network 131 is a public network that provides client device 120 with access to prediction server 112, data store 140, and other public computing devices. In some embodiments, network 131 is a private network that provides client device 120 with access to manufacturing equipment 124, validation wafer 128, enclosure system 130, data store 140, and other private computing devices. Network 131 may include one or more wide area networks (WANs), local area networks (LANs), wired networks (e.g., Ethernet networks, etc.), wireless networks (e.g., 802.11 networks or WiFi networks, etc.), cellular networks (e.g., Long Term Evolution (LTE) networks, etc.), routers, hubs, switches, server computers, cloud computing networks, and / or combinations thereof.

[0059] It should be noted that in some other embodiments, the functionality of server machines 170 and 180, as well as the functionality of prediction server 112, may be provided by fewer machines. For example, in some embodiments, server machines 170 and 180 may be combined into a single machine, while in other or similar embodiments, server machines 170 and 180, as well as prediction server 112, may be combined into a single machine.

[0060] In general, functionality described as being performed by server machine 170, server machine 180, and / or prediction server 112 in one implementation may also be performed by client device 120. Additionally, functionality attributed to a particular component may be performed by a different component or multiple components acting together.

[0061] In embodiments, a "user" is represented as a single individual (e.g., operator, technician, engineer, etc.). However, in other embodiments of the present disclosure, a "user" is an entity controlled by multiple users and / or automated sources. For example, a set of individual users aggregated as a group of administrators may be considered a "user."

[0062] 2A-B show a front view of enclosure system 200 (e.g., enclosure system 130 of FIG. 1A ) according to certain embodiments. FIG. 2C shows a cross-sectional top view of enclosure system 200 according to certain embodiments. FIG. 2D shows a top view of enclosure system 200 according to certain embodiments. In some embodiments, features having similar reference numbers to those in other figures include similar features and / or functionality as those described in other figures. In some examples, enclosure system 200 has similar features and / or functionality as enclosure system 130 of FIG. 1A . In some embodiments, enclosure system 200 is a side storage pod (e.g., SSP of FIG. 1A ).

[0063] 2A , enclosure system 200 includes walls including side walls 210 (e.g., side walls 210A-B, etc.), one or more rear walls 214 (see rear walls 214A-C in FIG. 2C ), and a bottom wall 220. Enclosure system 200 includes an enclosure lid 230 (e.g., a removable top wall, etc.) configured to couple (e.g., top-mounted, perimeter-mounted, etc.) to one or more walls (e.g., one or more side walls 210 and / or one or more rear walls 214, etc.) to at least partially enclose an interior volume of enclosure system 200. Enclosure lid 230 may be a removable lid for enclosure system 200. In some embodiments, enclosure lid 230 is configured to be removably attached to one or more walls.

[0064] In some embodiments, the enclosure lid 230 includes an overhead transport component 232 (e.g., for transporting the enclosure system 200, etc.). In some embodiments, the enclosure system 200 has one or more windows (e.g., observation windows, etc.).

[0065] In some embodiments, the posts 240 are coupled to the bottom wall 220 (e.g., via a base connector and one or more fasteners, etc.). The posts 240 are removably coupled to the enclosure lid 230. The support structure 244 is coupled (e.g., via fasteners, etc.) to the posts 240 and / or to a wall (e.g., one or more side walls 210 and / or one or more back walls 214, etc.).

[0066] Support structures 244 are disposed within the interior volume of the enclosure system 200. Each set of one or more support structures 244 can be configured to support a corresponding object (e.g., the contents 113 of FIG. 1A , a process kit ring, a carrier, a process kit ring disposed on the carrier, a validation wafer, etc.).

[0067] In some embodiments, two or more support structures 244 (e.g., two shelves positioned opposite each other, a first shelf positioned adjacent to sidewall 210A and a second shelf positioned adjacent to sidewall 210B, etc.) support an object. In some embodiments, the first and second support structures 244 supporting the object are substantially mirror images of each other (e.g., the dimensions of the two support structures are substantially mirror images of each other, etc.).

[0068] In some embodiments, a single support structure 244 (e.g., a single shelf that wraps from side wall 210A to side wall 210B along one or more rear walls 214) supports the object. In some embodiments, support structure 244 has a first distal end proximate side wall 210A and a second distal end proximate side wall 210B. In some embodiments, support structure 244 is a U-shaped shelf (e.g., that wraps around the back of enclosure system 200).

[0069] In some embodiments, each support structure 244 is connected to one or more posts coupled to bottom wall 220. Each post can be removably interfaced with enclosure lid 230. In some embodiments, each post can be positioned adjacent side wall 210A or side wall 210B. In some embodiments, each support structure 244 is connected to one or more of side walls 210A and / or 210B. In some embodiments, a first set of posts 240 (e.g., a first pair of posts 240, two posts 240, etc.) are coupled to bottom wall 220 adjacent side wall 210A (e.g., via the same base connector, etc.), and a second set of posts 240 (e.g., a second pair of posts 240, two additional posts 240, etc.) are coupled to bottom wall 220 adjacent side wall 210B (e.g., via a different base connector, etc.). A set of support structures 244 (e.g., a pair of shelves, two shelves, a first shelf and a second shelf, a coplanar shelf, etc.) can be used to support objects (e.g., content 113, etc.). A first support structure 244 can be attached to a first set of columns 240, and a second support structure 244 can be attached to a second set of columns 240. The first subset of support structures 244 and the second subset of support structures 244 are oriented in opposite directions from each other within the interior space of enclosure system 200 (e.g., are mirror images of each other, etc.).

[0070] The support structures 244 are configured to support objects such as the carrier 250, one or more process kit rings 252 disposed on the carrier 250, the verification wafer 254, and substrates. In some embodiments, the verification wafer 254 is disposed on one or more first support structures 244 (e.g., one or more support structures 244 located closest to the enclosure lid 230). In some embodiments, the carrier is disposed on one or more second support structures 244, and the one or more process kit rings 252 are disposed on the carrier 250 without the process kit rings 252 contacting the one or more second support structures 244. Each support structure 244 may form a recess to guide the process kit ring 252 into the correct position on the carrier 250 when the enclosure system 200 is moved (e.g., shaken, moved rapidly, etc.). In some embodiments, the verification wafer 254 is disposed on one or more upper support structures 244. In some embodiments, the verification wafer 254 has a thickness of less than about 10 millimeters (mm). In some embodiments, the diameter of the verification wafer 254 substantially matches the diameter of the substrate (eg, about 300 mm or about 450 mm, etc.).

[0071] In some embodiments, the top window (e.g., disposed on the enclosure lid 230, etc.) is configured for orientation verification (e.g., automatic or manual orientation verification, etc.) of objects placed within the interior volume. In some embodiments, the rear window (e.g., disposed on the rear wall 214, etc.) is removable for orientation adjustment (e.g., manual or automatic orientation adjustment, etc.) of one or more objects.

[0072] In some embodiments, each of the process kit rings 252 has a corresponding flat portion (e.g., a flat interior portion, etc.) that is viewable through a top window, a sensor (e.g., an image sensor, etc.) of the enclosure system 200, and / or a sensor (e.g., an image sensor, etc.) of the verification wafer 254. In some embodiments, each of the process kit rings 252 includes a feature (e.g., a notch, a peripheral notch, a recess, a marking, a top surface peripheral notch, etc.) on a top surface (or bottom surface) of the process kit ring 252 that is viewable through a top window and / or a sensor of the enclosure system 200 or the verification wafer 254. In some embodiments, the flat portion and / or feature (e.g., on the top surface, etc.) of each of the process kit rings 252 is viewable contemporaneously (e.g., simultaneously, etc.) through a top window and / or a sensor of the enclosure system 200 or the verification wafer 254. In some embodiments, each carrier 250 has carrier features that are simultaneously visible through a top window and / or sensors of the enclosure system 200 or the verification wafer 254. In some embodiments, the carrier features of each carrier 250, features on the top surface of each process kit ring 252, and the flat portion of each process kit ring 252 are simultaneously visible through the top window and / or sensors of the enclosure system 200 or the verification wafer 254. In response to the flat portion of the process kit ring 252 not being in the correct position or the carrier features not being in the correct position, the back window 236 can be removed and the orientation of the process kit ring 252 and / or the carrier 250 can be adjusted. In response to features on the top of the process kit ring 252 not being visible through the top window and / or sensors of the enclosure system 200 or the verification wafer 254 (e.g., not facing up, upside down, etc.), the enclosure lid 230 and / or the enclosure door can be removed and the process kit ring 252 can be flipped over.

[0073] A corresponding upper surface of each post 240 can be configured to removably interface with a corresponding component of the enclosure lid 230. In some embodiments, the corresponding upper surface of each post 240 forms a tapered recess configured to receive a tapered protrusion (e.g., a fastener, etc.) coupled to the enclosure lid 230 to align each post 240 with the enclosure lid 230.

[0074] Each of the one or more support structures 244 can be configured to align an object (e.g., content 113 in FIG. 1A ), such as a carrier 250, a process kit ring 252, and / or a validation wafer 254. In some embodiments, each of the one or more support structures 244 includes alignment features and / or surfaces configured to align an object on the one or more support structures 244. If a robot arm mispositions an object on the one or more support structures 244 and / or if a transport in the enclosure system 200 moves the object, the alignment features and / or surfaces align the object to the correct position. In some embodiments, the one or more support structures 244 include a holding device configured to secure an object to the one or more support structures 244.

[0075] In some embodiments, the interior volume of enclosure system 200 is a mini-environment (e.g., a sealed environment, etc.). In some embodiments, the interior volume of enclosure system 200 is kept substantially particle-free (e.g., substantially contaminant-free, etc.). In some embodiments, enclosure system 200 includes a fan (e.g., on the top surface, etc.) that suppresses particles within the interior volume. In some embodiments, the interior volume is substantially (or completely) free of one or more of moisture, oxygen, particles (e.g., dust, etc.), etc.

[0076] One or more walls of the enclosure system 200 form or are coupled to a front interface. The front interface is configured to interface (e.g., seal, etc.) with a transfer door of the enclosure system 200 (e.g., to provide a sealed environment, etc.). The front interface is configured to interface (e.g., seal, etc.) with a substantially vertical portion of a load port of a substrate processing system. In response to the front interface sealing to the door or load port, the enclosure system 200 creates a sealed environment (e.g., gases and / or particles do not enter or exit the enclosure system 200 from the ambient environment external to the substrate processing system, etc.).

[0077] In some embodiments, the bottom wall 220 includes or is coupled to a base plate (e.g., an adapter plate, etc.). The base plate is configured to interface with a horizontal portion of the load port. The base plate has features (e.g., recesses, receptacles, kinematic interfaces, etc.) for receiving motion devices (e.g., kinematic pins, precisely positioned pins, etc.) of the horizontal portion of the load port. In some embodiments, the base plate is secured to the bottom wall 220 before interfacing the enclosure system 200 with the load port. In some embodiments, the base plate is secured to the load port, and then the bottom wall 220 is secured to the base plate. In some embodiments, the enclosure system 200 includes a seal (e.g., a crushable seal, a gasket, etc.) for sealing one or more openings in the bottom wall 220.

[0078] In some embodiments, one or more overhead transport components 232 (e.g., overhead transport flanges, etc.) or at least one handle (e.g., handles 212A and 212B, etc.) are coupled to one or more surfaces of enclosure system 200 for transport (automated transport, manual transport, etc.) of enclosure system 200. In some embodiments, overhead transport (OHT) component 232 is coupled (e.g., attached, etc.) to enclosure lid 230. In some embodiments, a first handle is located on sidewall 210A and a second handle is located on sidewall 210B.

[0079] In some embodiments, one or more purge adapters are disposed in the bottom wall 220 (e.g., inserted into openings formed in the bottom wall 220). The purge adapters are used for one or more purposes, such as filling the enclosure system 200 with a gas (e.g., nitrogen (N)), an inert gas, removing gas from the enclosure system, or passing gas through the enclosure system 200. The purge adapters extend through the base plate and are fluidly coupled to one or more gas or vacuum lines (e.g., to purge the enclosure system 200, create a vacuum within the enclosure system 200, fill the enclosure system 200 with a gas, etc.). Each purge adapter provides a seal to a corresponding opening in the bottom wall 220 (e.g., to provide a sealed environment, etc.). In some embodiments, the enclosure system 200 is sealed to a load port in response to being docked to the load port. The interior volume of the enclosure system 200 is configured to be purged via one or more purge adapters prior to opening the enclosure system 200 .

[0080] In some embodiments, the enclosure system 200 includes a charging assembly 225. The charging assembly 225 includes a charging coil 227 disposed on one or more first support structures 244. The charging assembly 225 provides electrical energy to a charging interface 256 of the verification wafer 254. In some embodiments, the one or more first support structures 244 are configured to support the verification wafer 254 within a threshold distance of the charging coil 227. In some embodiments, the threshold distance is approximately 5-9 millimeters. In some embodiments, the threshold distance is approximately 7 millimeters. In some embodiments, the threshold distance allows a robot arm (e.g., a transfer robot arm, an EFEM robot, etc.) to lift the verification wafer 254 from the one or more support structures 244 and remove the verification wafer 254 from the enclosure system 200 without the top surface (e.g., the charging interface 256, etc.) of the verification wafer 254 contacting the charging coil 227. Furthermore, the one or more first support structures 244 can be configured to align the charging interface 256 with the charging coil 227. The charging assembly 225 can include a rechargeable battery that stores electricity to charge the verification wafer 254. The charging assembly 225 can include a lithium-ion battery. The charging assembly 225 can include a battery bank. In some embodiments, the battery of the charging assembly 225 can have a capacity of approximately 10,000 milliamp-hours. The verification wafer 254 (e.g., the battery of the verification wafer 254) can be charged from the charging coil 227 via inductive charging. The verification wafer 254 can receive charge from the charging coil 227 via a charging interface 256 of the verification wafer 254 (e.g., a coil of the charging interface 256, etc.). In some embodiments, the charging assembly 225 can charge the electrical storage device (e.g., a battery, a supercapacitor, etc.) of the verification wafer 254 via wireless charging (e.g., inductive charging, etc.). Charging of the verification wafer 254 occurs in response to the verification wafer 254 being positioned within a threshold distance of the charging coil 227 and the charging interface 256 being aligned with the charging coil 227.Additionally, in some embodiments, charging of validation wafer 254 occurs in response to a command from a controller (eg, the controller of charging assembly 225, etc.).

[0081] In some embodiments, the charging assembly 225 receives power from an external source (e.g., a wall outlet at the substrate fabrication facility, etc.). In some embodiments, the charging assembly 225 receives power from a substrate processing system (e.g., processing system 100A, etc.) via an electrical connection between the enclosure system 200 and an EFEM interface (e.g., load port 129 in FIG. 1A, etc.). In some embodiments, the charging assembly 225 includes a controller (e.g., a processing device, a microcontroller, a computing device, etc.). The controller can manage the charging of the validation wafer 254. In some embodiments, the controller tracks inventory of the enclosure system 200 (e.g., inventory of process kit rings 252, inventory of validation wafers 254, etc.) based on performed maintenance procedures, sensor data (e.g., image data from sensors in the enclosure system 200 and / or the validation wafer 254, etc.), and / or user input.

[0082] In some embodiments, enclosure system 200 includes a radio frequency identification (e.g., RFID 221) held by RFID holder 222. RFID 221 can store and / or broadcast data related to enclosure system 200. For example, RFID 221 can store and / or broadcast data indicating the enclosure type of enclosure system 200. In another example, RFID 221 can store and / or broadcast data indicating the inventory of enclosure system 200 (e.g., inventory of process kit rings 252, verification wafers 254, etc.). In some embodiments, the data stored by RFID 221 can be read by an RFID reader (e.g., RFID reader of load port 129 in FIG. 1A, etc.). In some embodiments, RFID holder 222 holds RFID 221 in a horizontal or vertical orientation. RFID holder 222 can hold RFID 221 near rear wall 214. In some embodiments, the RFID holder 222 is coupled to the bottom wall 220 .

[0083] 2B , in some embodiments, the charging assembly 225 includes multiple charging coils 227 (e.g., disposed on one or more corresponding support structures 244). Charging coil 227A is disposed below the enclosure lid 230 and above one or more support structures 244A configured to support a first object (e.g., verification wafer 254A, etc.). Charging coil 227B may also be disposed below one or more support structures 244A (e.g., one or more upper support structures, etc.). Charging coil 227B is disposed above one or more support structures 244B configured to support a second object (e.g., verification wafer 254B, etc.). One or more support structures 244B can be configured to support the verification wafer 254B within a threshold distance of the second charging coil 227B. In some embodiments, the one or more support structures 244B can be configured to position the verification wafer 254B to align the charging interface 256 of the verification wafer 254B with the charging coil 227B. The verification wafer 254B is supported by one or more support structures 244B within a threshold distance from the second charging coil 227B and can be charged with the charging interface of the verification wafer 254B aligned with the charging coil 227B. In some embodiments, the one or more charging coils 227B are supported by a charging assembly support structure 229 (e.g., positioned along the back wall 214 or the side wall 210). In some embodiments, the charging assembly support structure 229 includes electrical connections for electrically coupling the one or more charging coils 227 to the battery of the charging assembly 225B.

[0084] 2C , the verification wafer 254 can include a user interface. In some embodiments, the user interface includes a switch 255 (e.g., an on / off switch, etc.) and / or an indicator 257. In some embodiments, the switch 255 is a power switch for the verification wafer 254. For example, the verification wafer 254 can be turned off when the switch 255 is in the “off” position. Additionally, the verification wafer 254 can be turned on when the switch 255 is in the “on” position. In some embodiments, the switch 255 is operated by a user (e.g., a technician, an operator, etc.) when the verification wafer 254 is outside the enclosure system 200. In some embodiments, the switch 255 is operated by a user when the verification wafer 254 is supported by one or more support structures 244.

[0085] In some embodiments, indicator 257 is a light-emitting diode (LED). In some embodiments, the color, blinking pattern, and / or brightness of indicator 257 changes to indicate the state of verification wafer 254. For example, in a first state, indicator 257 can have a first brightness, blinking pattern, and / or color to indicate that verification wafer 254 is on. In a second state, indicator 257 can have a second brightness, blinking pattern, and / or color to indicate that verification wafer 254 is in a low-power state. In a third state, indicator 257 can have a third brightness, blinking pattern, and / or color to indicate to a user that verification wafer 254 is in an external power state (e.g., verification wafer 254 is charging, etc.). In a fourth state, indicator 257 can have a fourth brightness, blinking pattern, and / or color to indicate an error (e.g., data transmission or reception error, sensor operation error, data processing error, etc.). In some embodiments, indicator 257 includes multiple LEDs. Additionally, in some embodiments, indicator 257 may include a graphical user interface (GUI). In some embodiments, switch 255 may be included in the GUI of verification wafer 254.

[0086] 2D , in some embodiments, charging assembly 225 is disposed at least partially above, below, and / or within enclosure lid 230 of enclosure system 200. In some embodiments, the non-charging enclosure lid can be removed from enclosure system 200, and enclosure lid 230 including charging assembly 225 can be attached to enclosure system 200.

[0087] Charging assembly 225 includes charging coil 227, battery 231, controller 233, and / or switch 235 (e.g., an on / off switch, etc.). In some embodiments, battery 231, controller 233, and / or associated electronics (e.g., a printed circuit board (PCB), electronic connections, etc.) are substantially contained within a housing of charging assembly 225. In some embodiments, charging coil 227 is disposed over charging interface 256 of verification wafer 254. Charging coil 227 can receive electricity from battery 231. In some embodiments, charging coil 227 receives electricity from battery 231 via controller 233. In some embodiments, switch 235 is an on / off switch (e.g., an on / off switch of charging assembly 225, etc.).

[0088] 3 shows a schematic diagram of a charging assembly 300 of an enclosure system (e.g., charging assembly 225 of FIGS. 2A-D, etc.) according to certain embodiments. Charging assembly 300 may be a charging assembly of an enclosure system (e.g., enclosure system 130 of FIGS. 1A-B, enclosure system 200 of FIGS. 2A-D, etc.). In some embodiments, charging assembly 300 may be a charging assembly of a side storage pod (e.g., SSP of FIG. 1A, etc.). Charging assembly 300 may be configured to provide electrical energy to a verification wafer (e.g., verification wafer 254 of FIGS. 2A-D, etc.).

[0089] In some embodiments, charging assembly 300 includes battery 310 (e.g., battery 231 in FIG. 2D ), controller 320 (e.g., controller 233 in FIG. 2D ), charging coil 330 (e.g., charging coil 227 in FIGS. 2A, 2B, and 2D ), and switch 340 (e.g., switch 235 in FIG. 2D ). In some embodiments, one or more components of charging assembly 300 are included on or coupled to a PCB. In some embodiments, charging assembly 300 includes one or more PCBs. Battery 310 can store electrical energy used to charge the verification wafer. In some embodiments, battery 310 is a rechargeable battery. Battery 310 can receive electrical energy from an external source (e.g., a wall outlet at the substrate fabrication facility, an electrical connection in the EFEM, etc.). Battery 310 can include one or more sensors for monitoring the status of battery 310 (e.g., state of charge, temperature status, etc.). In some embodiments, battery 310 is a lithium-ion battery. In some embodiments, battery 310 can have a capacity of up to approximately 10,000 milliamp hours. In some embodiments, battery 310 is configured to be able to be shipped via air transport (e.g., battery 310 meets certain specifications, such as size, weight, capacity, etc., suitable for air transport).

[0090] In some embodiments, the battery 310 is electrically connected to the charging coil 330 via one or more electrical connections. In some embodiments, the battery 310 is electrically connected to the controller 320, and the charging coil 330 is also electrically connected to the controller 320. In some embodiments, the battery 310 is electrically connected to the controller 320 by a battery ground wire 312 and a battery hot wire 314. The battery hot wire 314 may connect the battery 310 to a first pin of a connector J1 connected to the controller 320 (e.g., located on a PCB of the controller 320). The battery ground wire 312 may connect the battery 310 to a second pin of the connector J1. In some embodiments, the battery hot wire 314 and / or the battery ground wire 312 are 26-gauge wires.

[0091] In some embodiments, charging coil 330 is electrically coupled to controller 320 by charging coil hot wire 334 and charging coil ground wire 332. Charging coil hot wire 334 can be connected to a first pin of connector J2 coupled to controller 320 (e.g., located on a PCB of controller 320). Charging coil ground wire 332 can be connected to a second pin of connector J2. In some embodiments, charging coil hot wire 334 carries a current with a voltage of approximately 3-10 volts in response to controller 320 charging the verification wafer via charging coil 330. In some embodiments, charging coil hot wire 334 carries a current with a voltage of approximately 5 volts in response to controller 320 charging the verification wafer via charging coil 330. In some embodiments, charging coil hot wire 334 and / or charging coil ground wire 332 are 24-gauge wire.

[0092] In some embodiments, the switch 340 is electrically coupled to the controller 320 by a switch hot wire 344 and a switch ground wire 342. The switch hot wire 344 can be connected to a first pin of a connector J3 coupled to the controller 320 (e.g., located on a PCB of the controller 320). The switch ground wire 342 can be connected to a second pin of the connector J3. Furthermore, the switch 340 includes multiple pins. In some embodiments, a first pin 345 of the switch 340 is electrically coupled to the switch ground wire 342. A second pin 346 of the switch 340 is electrically coupled to the switch hot wire 344. A third pin 347 of the switch 340 can be left unconnected. In some embodiments, the switch 340 controls the state of the controller 320. For example, the switch 340 can control the on / off state of the controller 320. In a first position, the third pin 347 of the switch 340 is electrically connected to the first pin 345, and the third pin 347 is electrically grounded. In the second position, the second pin 346 of the switch 340 is electrically connected to the first pin 345, and the second pin 346 is electrically grounded. The controller 320 can be turned on and / or off based on the position of the switch 340. The controller 320 can be turned on and / or off based on whether the first pin of the connector J3 is electrically grounded (e.g., whether the switch hot wire 344 is electrically connected to the switch ground wire 342 via the first pin 345 and the second pin 346 of the switch 340). In some embodiments, the switch 340 is a pushbutton switch. In some embodiments, the switch 340 is a single-pole, double-throw switch (e.g., a switch that has only one input and can be connected to and switched between two outputs). In some embodiments, the switch 340 is a toggle switch (e.g., an electrical switch that is operated by moving a lever back and forth to open or close an electrical circuit). In some embodiments, the switch 340 is controlled wirelessly.

[0093] In some embodiments, the enclosure system (e.g., including the charging system 300) includes one or more sensors. In some embodiments, the charging system 300 includes one or more sensors. In some embodiments, the controller 320 can receive sensor data from the battery 310, sensors in the enclosure system, sensors in the charging system 300, and / or the validation wafer. In some embodiments, the controller 320 includes a microcontroller 321 (e.g., a processing device, processor, computing device, etc.). The sensor data can indicate one or more parameters (e.g., a charge level of the battery 310, a lifespan of the battery 310, a total charge cycles of the battery 310, etc.). The microcontroller 321 can determine the status of the battery 310, the enclosure system, components of the substrate processing system, and / or the validation wafer based on the received sensor data. For example, the microcontroller 321 can determine that the battery 310 is in a low charge state based on sensor data received from one or more battery sensors. In another example, the microcontroller 321 can determine that the validation wafer is in a low charge state based on sensor data received from the validation wafer. In some embodiments, the microcontroller 321 determines the status of one or more components (e.g., process kit ring, processing chamber, etc.) based on the sensor data received from the verification wafer. In some embodiments, the microcontroller 321 performs corrective action based on the determined status. For example, the microcontroller 321 can charge the verification wafer (e.g., via the charging coil 330, etc.). In another example, the microcontroller 321 can stop charging the verification wafer based on its determination (e.g., the verification wafer is fully charged, the verification wafer's electrical storage device is overheating, etc.). In some embodiments, the controller 320 (e.g., the microcontroller 321, etc.) causes the verification wafer to charge in response to the verification wafer being within a threshold distance of the charging coil 330.In some embodiments, controller 320 charges the verification wafer in response to the verification wafer's charging interface being aligned with charging coil 330. Controller 320 can start and / or stop the flow of electricity from battery 310 to charging coil 330. In some embodiments, controller 320 regulates the charging of the verification wafer to prevent the verification wafer from being undercharged and / or overcharged. In some embodiments, controller 320 provides a warning based on sensor data. In some embodiments, controller 320 causes the enclosure system to dock (e.g., to a load port, etc.) for a threshold time to charge battery 310 to a threshold charge level.

[0094] In some embodiments, the charging coil 330 is configured to electrically charge the verification wafer through inductive charging. The charging coil 330 can be energized in response to electricity supplied by the controller 320 (e.g., via the charging coil hot wire 334). The charging coil 330 can wirelessly charge the verification wafer. In some embodiments, the charging coil 330 can wirelessly charge the verification wafer using resonant inductive coupling. The charging coil 330 can wirelessly charge the verification wafer using electromagnetic induction between planar coils (e.g., between the charging coil 330 and a corresponding coil of the verification wafer). In some embodiments, the charging coil 330 can generate an oscillating magnetic field. The oscillating magnetic field can induce an alternating current in a receiving coil (e.g., a coil of the verification wafer) via Faraday's law of induction. In some embodiments, the charging coil 330 wirelessly charges the verification wafer using the Qi standard. In use, the charging coil 330 can be coupled to the bottom surface of the top wall of the enclosure system.

[0095] FIG. 4 shows a side view of a charging assembly 400 of an enclosure system (e.g., charging assembly 225 of FIGS. 2A-2D, charging assembly 300 of FIG. 3, etc.) according to certain embodiments. In some embodiments, charging assembly 400 is a charging assembly of a side storage pod (e.g., SSP of FIG. 1A, etc.). In some embodiments, a verification wafer is supported by one or more support structures within a threshold distance 460 of a charging coil 430. The top surface of the verification wafer (e.g., wafer top surface 455, etc.) may be within the threshold distance 460 from the surface of the charging coil 430. The charging coil 430 may be coupled to a charging coil support 432 of an enclosure system (e.g., enclosure system 130 of FIGS. 1A-1B, enclosure system 200 of FIGS. 2A-2D, etc.). The charging coil support 432 may be coupled to the underside of a lid of the enclosure system. In some embodiments, charging coil support 432 can be coupled to an enclosure system (e.g., enclosure system 200 of FIG. 2B ) between one or more support structures (e.g., support structures 244A-F of FIG. 2B ). To initiate verification charging, in some embodiments, charging interface 456 is aligned with charging coil 430. Charging interface 456 may be located within a threshold distance 460 of charging coil 430. In some embodiments, threshold distance 460 is approximately 6-8 millimeters (mm). In some embodiments, wafer top surface 455 is positioned 5-6 mm below charging coil support 432. Charging coil support 432 may have a thickness of approximately 0.5 mm. In some embodiments, charging coil support 432 is the bottom wall of charging assembly 400. In some embodiments, the bottom surface of charging coil support 432 is positioned approximately 5-6 mm above wafer top surface 455. In some embodiments, the wafer top surface 455 is positioned a threshold distance below the bottom surface of the charging coil support 432 to facilitate a robotic arm lifting the verification wafer off the support structure and removing the verification wafer from the enclosure system without the wafer top surface 455 contacting the bottom surface of the charging coil support 432.

[0096] FIG. 5 illustrates a flow diagram of a method 500 for performing a corrective action (e.g., associated with an enclosure system, associated with a substrate processing system, associated with a verification wafer, etc.) according to certain embodiments. In some embodiments, one or more operations of method 500 are performed by processing logic, which may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, a processing device, etc.), software (e.g., instructions executed on a processing device, a general-purpose computer system, or a dedicated machine, etc.), firmware, microcode, or a combination thereof. In some embodiments, method 500 may be performed at least in part by prediction system 110 of FIG. 1B. In some embodiments, method 500 may be performed at least in part by corrective action component 123. In some embodiments, method 500 may be performed at least in part by a controller of an enclosure system (e.g., controller 320 of FIG. 3, etc.). In some embodiments, method 500 may be performed at least in part by a processing device for a verification wafer. In some embodiments, method 500 may be performed, at least in part, by a controller of a substrate processing system (e.g., controller 109 of processing system 100A of FIG. 1A ). In some embodiments, method 500 may be performed, at least in part, by a controller of substrate processing equipment (e.g., a controller controlling movement of an enclosure system to a different substrate processing system). In some embodiments, method 500 may be performed, at least in part, by a controller of an EFEM. Although shown in a particular sequence or order, unless otherwise specified, the order of processes can be changed. Therefore, the illustrated embodiments should be understood as examples only, and the illustrated processes may be performed in a different order, and some processes may be performed in parallel. Furthermore, in various embodiments, one or more processes may be omitted. Therefore, not all processes are used in all embodiments.In some embodiments, a non-transitory storage medium stores instructions that, when executed by a processing device (e.g., prediction system 110, server machine 180, prediction server 112, manufacturing equipment 124, verification wafer 128, enclosure system 130, client device 120, controller 109, etc.), cause the processing device to perform method 500.

[0097] For ease of explanation, method 500 is shown and described as a series of operations. However, operations in accordance with the present disclosure may be performed in various orders and / or simultaneously and in parallel with other operations not shown and described herein. Moreover, not all illustrated operations may be performed to implement method 500 in accordance with the disclosed subject matter. Furthermore, those skilled in the art will understand and appreciate that method 500 may also be represented as a series of interrelated states via a state diagram or events.

[0098] At block 502, processing logic (e.g., of an enclosure system, a substrate processing system, a substrate processing facility, an EFEM, etc.) receives a first subset of sensor data from a validation wafer. In some embodiments, the processing logic receives the first subset via wireless communication.

[0099] In some embodiments, the first subset is associated with a charge state of at least one electrical storage device (e.g., a battery, a supercapacitor, etc.) of the validation wafer. In some embodiments, the validation wafer is configured to be transferred by a robot of an EFEM of the substrate processing system from one or more support structures (e.g., a pair of shelves, a U-shaped shelf, etc.) disposed within the interior volume formed by the enclosure system.

[0100] In some embodiments, the first subset may include battery data associated with a charge state of a supercapacitor of the verification wafer (e.g., a charge level of the supercapacitor, etc.). In some embodiments, the first subset may include temperature data. For example, the first subset may include temperature data of an electrical storage device (e.g., a supercapacitor, etc.) of the verification wafer. In an additional example, the first subset may be associated with a clarity score of one or more images captured by an imaging device (e.g., a camera, etc.) of the verification wafer. The clarity score may be an indication of how many “sharp” edges are present in the image. For example, a higher clarity score indicates more edges are present. The clarity score may be unitless. In some embodiments, the first subset may indicate an amount of electricity required to fully charge the verification wafer. In some embodiments, the processing device receives the first subset from the second verification wafer.

[0101] In some embodiments, the first subset includes image data. The image data may be image data associated with a process kit ring disposed within a processing chamber associated with the enclosure system. For example, the image data may be associated with the placement and / or condition of the process kit ring within the processing chamber. The image data may be associated with corrosion and / or erosion of the process kit ring exposed to one or more plasma processes within the processing chamber over time.

[0102] The first subset may include one or more of alignment data (e.g., a process kit ring positioned within a processing chamber), image data (e.g., one or more captured images), light beam data (e.g., laser light beam data), vibration data, temperature data, humidity data, process gas data, particle data, pressure data, proximity data, displacement data, impedance data, acoustic data, placement data, etc.

[0103] At block 504, the processing logic receives a second subset of sensor data from a charging assembly (e.g., a controller of the charging assembly, etc.) of the enclosure system. In some embodiments, the processing device receives the second subset via wireless communication. In some embodiments, the second subset includes battery data (e.g., charge data, temperature data, cycle data, age data, etc.) associated with a battery of the charging assembly. As an example, the second subset may include data associated with a charge level (e.g., state of charge, etc.) of the charging assembly battery. In some embodiments, the second subset may be associated with a charge level stored in the battery. As a further example, the second subset may include temperature data associated with the battery (e.g., used to determine if the battery is overheating, etc.). In some embodiments, one or more sensors (e.g., image sensors, etc.) of the enclosure system provide a second subset of sensor data associated with an inventory of the enclosure system. The inventory of the enclosure system may include a quantity and / or location of one or more objects (e.g., verification wafers, process kit rings, etc.) disposed on one or more support structures of the enclosure system.

[0104] In some embodiments, the second subset includes identifier data received from an RFID tag (such as RFID 221 in FIG. 2A) of the enclosure system. For example, the identifier data may include inventory data for the enclosure system. The identifier data may include data associated with the type of enclosure system. In some embodiments, the identifier data may include data associated with the configuration of the enclosure system.

[0105] At block 506, processing logic causes a corrective action associated with the substrate processing system. In some embodiments, causing the corrective action to be performed is based on the first sensor data. In some embodiments, causing the corrective action to be performed is based on a first subset of the first sensor data and / or a second subset of the first sensor data. In some embodiments, the corrective action includes one or more of providing a notification (e.g., a notification on a GUI associated with the enclosure system for a user to view), transporting a verification wafer to the enclosure system for charging, maintaining or replacing the verification wafer (e.g., maintaining components of the verification wafer (e.g., camera, sensor, etc.), replacing components of the verification wafer, replacing the verification wafer, etc.), and / or replacing a process kit ring disposed within the processing chamber. In some embodiments, the corrective action includes placing the enclosure system in a charging position for a threshold time to at least partially charge a battery of the enclosure system (e.g., a battery in a charging assembly of the enclosure system, etc.), performing maintenance or replacing a portion of the enclosure system (e.g., repairing and / or replacing a battery in a charging assembly of the enclosure system, etc.), and / or moving the enclosure system to a predetermined location. In some embodiments, the predetermined location is a load port (e.g., a location adjacent to the EFEM, etc.). In some embodiments, the predetermined location is a maintenance location. In some embodiments, the predetermined location is a charging location. In some embodiments, the corrective action includes charging the enclosure system via an electrical connection between the enclosure system and a load port (e.g., of the EFEM, etc.). In some embodiments, the corrective action is associated with a second verification wafer of the enclosure system.

[0106] In some embodiments, the processing logic determines performance data or predictive data based on the sensor data, determines corrective actions based on the performance data or predictive data, and causes the corrective actions to be executed. For example, the processing logic may determine, based on the sensor data received from the validation wafer, that the charge level of the validation wafer's supercapacitor is below a predetermined threshold. The processing logic may then determine that the validation wafer needs to be charged (i.e., that the validation wafer's supercapacitor needs to be charged). The processing logic may then cause the validation wafer to be charged (e.g., by a charging assembly of the enclosure system, etc.). The processing logic may cause a notification to be provided indicating that the validation wafer needs to be charged.

[0107] In another example, processing logic may determine, based on image data from the verification wafer, that a process kit ring disposed in a processing chamber of a substrate processing system is worn. Processing logic may then determine that the process kit ring needs to be replaced and / or that the process kit ring will need to be replaced in the future. Processing logic may then cause the process kit ring to be replaced. Processing logic may cause a notification to be provided indicating that the process kit ring needs to be replaced.

[0108] In a further example, the processing logic may determine that the charge of a battery in the enclosure system charging assembly is below a predetermined threshold. The processing logic may then determine that the battery needs to be charged. The processing logic may then cause the battery to be charged (e.g., via an electrical connection between the enclosure system and the EFEM, via an electrical connection between the enclosure system and the substrate processing equipment, etc.). The processing logic may provide a notification indicating that the battery needs to be charged.

[0109] In some embodiments, the processing logic may determine the performance data and / or the prediction data by executing one or more machine learning models (e.g., one or more of the machine learning models described with reference to Figures 6A-C below).

[0110] 6A-C are flow diagrams of methods 600A-C relating to machine learning models (e.g., generating prediction data related to an enclosure system), according to certain embodiments. Methods 600A-C may be performed by processing logic including hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, a processing device, etc.), software (e.g., instructions running on a processing device, a general-purpose computer system, or a dedicated machine, etc.), firmware, microcode, or a combination thereof. In some embodiments, methods 600A-C may be performed in part by prediction system 110. Method 600A may be performed in part by prediction system 110 (e.g., server machine 170 and training set generator 172 of FIG. 1, etc.). Prediction system 110 may use method 600A to generate a data set for at least one of training, validating, or testing a machine learning model, according to embodiments of the present disclosure. Method 600B may be performed by server machine 180 (e.g., training engine 182, etc.). Method 600C may be performed by prediction server 112 (e.g., prediction component 114, etc.). In some embodiments, a non-transitory storage medium stores instructions that, when executed by a processing device (e.g., prediction system 110, server machine 180, prediction server 112, etc.), cause the processing device to perform one or more of methods 600A-C. In some embodiments, the storage medium is a non-transitory machine-readable storage medium that stores instructions that, when executed by a processing device (e.g., prediction system 110, client device 120, etc.), cause the processing device to perform methods 600A-C.

[0111] For ease of explanation, methods 600A-C are shown and described as a series of operations. However, operations in accordance with the present disclosure may be performed in various orders and / or simultaneously and in parallel with other operations not shown and described herein. Moreover, not all illustrated acts may be performed to implement methods 600A-C in accordance with the disclosed subject matter. Furthermore, those skilled in the art will understand and appreciate that methods 600A-C may be represented as a series of interrelated states via a state diagram or events.

[0112] FIG. 6A is a flow diagram of a method 600A for generating a dataset for training a machine learning model (e.g., model 190 of FIG. 1B) to predict performance data associated with an enclosure system, according to certain embodiments.

[0113] Referring to FIG. 6A, in some embodiments, at block 601, processing logic implements method 600A to initialize a training set T to an empty set.

[0114] At block 602, processing logic generates a first data input (e.g., a first training input, a first validation input, etc.) that may include sensor data (e.g., sensor data 141 of FIG. 1B, etc.). In some embodiments, the first data input may include a first feature set for a type of data, and the second data input may include a second feature set for the type of data.

[0115] At block 603, processing logic generates a first target output for one or more data inputs (e.g., a first data input, etc.). In some embodiments, the first target output is performance data (e.g., performance data 144 in FIG. 1B, etc.).

[0116] At block 604, processing logic optionally generates mapping data indicating an input / output mapping. The input / output mapping (or mapping data) may refer to a data input (e.g., one or more data inputs described herein), a target output for the data input, and an association between the data input and the target output.

[0117] At block 605, processing logic, in some embodiments, adds the mapping data generated at block 604 to dataset T.

[0118] At block 606, processing logic branches based on whether dataset T is sufficient for at least one of training, validation, and / or testing of machine learning model 190 of FIG. 1B. If so, execution proceeds to block 607; otherwise, execution returns to block 602. It should be noted that while in some embodiments, the sufficiency of dataset T may be determined solely based on the number of inputs (which in some embodiments are mapped to outputs) in the dataset, other embodiments may determine the sufficiency of dataset T based on one or more other criteria (e.g., a measure of diversity of the data examples, accuracy, etc.) in addition to or instead of the number of inputs.

[0119] At block 607, processing logic provides dataset T (e.g., to server machine 180 of FIG. 1B ) for training, validating, and / or testing machine learning model 190. In some embodiments, dataset T is a training set and is provided to training engine 182 of server machine 180 to perform training. In some embodiments, dataset T is a validation set and is provided to validation engine 184 of server machine 180 to perform validation. In some embodiments, dataset T is a test set and is provided to test engine 188 of server machine 180 to perform testing.

[0120] Over many training sets, the machine learning model selects an appropriate value for a parameter that controls the number of non-zero coefficients in the reduced-dimensional model. After block 607, the machine learning model (e.g., machine learning model 190) may be either trained using training engine 182 of server machine 180, validated using validation engine 184 of server machine 180, or tested using test engine 188 of server machine 180. The trained machine learning model may be executed by prediction component 114 (of prediction server 112) to generate current performance data 146 for taking corrective actions related to enclosure system 130 and / or validation wafer 128.

[0121] FIG. 6B is a method 600B for training a machine learning model (such as, for example, model 190 of FIG. 1B) to generate predictive data (such as, for example, associated with an enclosure system) according to certain embodiments.

[0122] 6B , at block 610 of method 600B, processing logic receives historical sensor data. The historical sensor data may be associated with one or more historical validation wafers or one or more historical enclosure systems. In some embodiments, the historical sensor data is associated with an electrical storage device of the historical validation wafer. In some embodiments, the historical sensor data (e.g., historical image data, etc.) may be associated with one or more historical components of the substrate processing system (e.g., historical process kit rings, etc.). In some embodiments, the historical sensor data is associated with a component disposed in a processing chamber (e.g., process kit rings, etc.). The historical sensor data may be retrieved by processing logic from a memory (e.g., data store 140 of FIG. 1B ) rather than directly from the validation wafer.

[0123] At block 612, processing logic receives historical performance data associated with the historical sensor data. In some embodiments, the historical performance data may include corrective actions associated with the historical sensor data. For example, the historical performance data may include a validation wafer charging action associated with historical sensor data indicating a charge state of a historical validation wafer. In another example, the historical performance data may include a process chamber maintenance operation (e.g., replacing a process kit ring disposed in a process chamber) associated with historical sensor data indicating a status of a chamber component (e.g., a process kit ring, etc.). In some embodiments, the historical performance data may include an omission associated with the historical sensor data. For example, the historical performance data may indicate that a corrective action associated with historical sensor data indicating a charge state of a validation wafer was not performed.

[0124] At block 614, processing logic trains a machine learning model (e.g., model 190 of FIG. 1B ). The machine learning model is trained with data inputs including historical sensor data. The machine learning model is trained with target output data including historical performance data. In some embodiments, the historical performance data corresponds to corrective actions performed on the processing chamber and / or validation wafers. The training data input to the machine learning model is mapped to the training target outputs. The machine learning model is trained to predict prediction data used to perform the corrective actions. In some embodiments, the machine learning model is trained to output predicted performance data (e.g., data indicative of one or more corrective actions to be performed).

[0125] In some embodiments, multiple machine learning models may be part of a single composite machine learning model, in which case training one component of the composite model may involve receiving output from another component of the model as training input to the component of the model being trained.

[0126] At block 616, the machine learning model may be retrained using additional data. The machine learning model may be retrained using data inputs including sensor data (e.g., the first and / or second subset of the first sensor data, etc.). The machine learning model may be retrained using target output data including performance data. The machine learning model may be retrained to predict further predictive data related to corrective actions to be taken. In some embodiments, the machine learning model may be continuously trained to account for drift in manufacturing equipment, sensors, metrology equipment, validation wafers, etc., or to reflect changes in procedures, recipes, etc.

[0127] 6C illustrates a method 600C for generating predictive data (e.g., data related to an enclosure system, etc.) using a trained machine learning model (e.g., model 190 of FIG. 1B, etc.) according to certain embodiments. In some embodiments, the trained machine learning model can be configured to output predictive data (e.g., predictive data related to corrective actions for the enclosure system, etc.).

[0128] 6C , in block 620 of method 600C, processing logic receives sensor data. The processing logic may receive a first subset of sensor data from a validation wafer and / or a second subset of sensor data from a charging assembly of an enclosure system. The type of sensor data may correspond to that provided in block 610 of FIG. 6B to train the machine learning model. Block 620 may be similar to block 502 and / or block 504.

[0129] At block 622, processing logic provides the sensor data as input to a trained machine learning model (e.g., such as model 190 of FIG. 1B). The processing logic may provide one or more of the first subset and / or the second subset as input to the trained machine learning model. The machine learning model may be trained according to the embodiments described with respect to FIGS. 6A and 6B. For example, the machine learning model may be trained to generate predictive data (e.g., data corresponding to one or more corrective actions), as described above.

[0130] At block 624, processing logic obtains one or more outputs of the machine learning model. In some embodiments, the one or more outputs of the machine learning model include predictive data corresponding to one or more corrective actions. In some embodiments, processing logic determines the predictive data based on the one or more outputs of the machine learning model. The predictive data may be a prediction of performance data. For example, the predictive data may be associated with a prediction that a supercapacitor (e.g., of a validation wafer) will run out of charge after a certain time or a certain number of cycles (e.g., a validation wafer inspection cycle). In another example, the predictive data may be associated with a prediction that a process kit ring (e.g., of a processing chamber) will wear beyond a predetermined threshold at a certain time. In some embodiments, the one or more outputs of the machine learning model indicate one or more corrective actions to be performed on the processing chamber and / or the validation wafer.

[0131] At block 626, processing logic determines a corrective action to be taken based on the prediction data. In some embodiments, processing logic causes the corrective action associated with the prediction data to be performed. In one example, processing logic may determine that the supercapacitor of the validation wafer should be charged for a predetermined time or a predetermined number of cycles or before a predetermined number of cycles. In another example, processing logic may determine that the validation wafer should be docked longer (e.g., in an enclosure system, etc.) to receive a charge from an enclosure system charging assembly. In another example, processing logic may determine that a process kit ring should be replaced (e.g., as in the example above) based on the prediction data.

[0132] At block 628, processing logic performs corrective action related to the substrate processing system. Block 628 may be similar to block 506 of FIG. 5 . For example, processing logic may cause the verification wafer's supercapacitor to charge. In another example, processing logic may cause the verification wafer to dock longer to receive more charge from the enclosure system charging assembly. In another example, processing logic may cause the process kit ring in the processing chamber to be replaced.

[0133] 7 is a block diagram illustrating a computer system 700 according to an aspect of the present disclosure. In some embodiments, computer system 700 is client device 120 (e.g., FIG. 1B, etc.). In some embodiments, computer system 700 is controller 109 (e.g., FIGS. 1A-B, etc.). In some embodiments, computer system 700 is a processing device for verification wafer 128 (e.g., FIG. 1B, etc.). In some embodiments, computer system 700 is a processing device for enclosure system 130 (e.g., microcontroller 321 in FIGS. 1A-B, FIG. 3, etc.). Computer system 700 can incorporate cloud-based functionality.

[0134] In some embodiments, computer system 700 is connected to other computer systems (e.g., via a network such as a local area network (LAN), an intranet, an extranet, or the Internet). Computer system 700 operates as a server or a client computer in a client-server environment, or as a peer computer in a peer-to-peer or distributed network environment. In some embodiments, computer system 700 is provided by a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a mobile phone, a web appliance, a server, a network router, switch, or bridge, or any device capable of executing a set of instructions (sequential or otherwise) that specify actions to be performed by that device. Furthermore, the term "computer" includes any collection of computers that individually or collectively execute a set (or sets) of instructions to perform one or more of the methodologies described herein.

[0135] In some embodiments, computer system 700 includes a processing device 702, volatile memory 704 (e.g., random access memory (RAM)), non-volatile memory 706 (e.g., read-only memory (ROM) or electrically erasable programmable ROM (EEPROM)), and / or a data storage device 718, which communicate with each other via a bus 708.

[0136] In some embodiments, processing device 702 is provided by one or more processors, such as a general-purpose processor (e.g., a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor that executes other types of instruction sets, or a microprocessor that executes a combination of multiple types of instruction sets, etc.) or a special-purpose processor (e.g., an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), or a network processor, etc.). In some embodiments, processing device 702 is provided by one or more of a single processing device, multiple processing devices, a single processing device with multiple processing cores, etc.

[0137] Additionally, in some embodiments, computer system 700 includes a network interface device 722 (e.g., coupled to a network 774). In some embodiments, computer system 700 includes one or more input / output (I / O) devices. Also, in some embodiments, computer system 700 includes a video display unit 710 (e.g., a liquid crystal display (LCD)), an alphanumeric input device 712 (e.g., a keyboard), a cursor control device 714 (e.g., a mouse), and / or a signal generating device 720.

[0138] In some embodiments, a data storage device 718 (e.g., disk drive storage, fixed and / or removable storage devices, fixed disk drives, removable memory cards, optical storage, network attached storage (NAS), and / or storage area networks (SANs), etc.) includes a non-transitory computer-readable storage medium 724 that stores instructions 726 encoding any one or more of the methods or functions described herein, including instructions encoding the components of FIG. 1B (e.g., corrective action component 123) and instructions for performing the methods described herein. In some embodiments, the processing device 702 includes the corrective action component 123. In some embodiments, the sensor data 141, the performance data 144, and / or the prediction data 147 are stored in the data storage device 718.

[0139] In some embodiments, the instructions 726 reside, completely or partially, within the volatile memory 704 and / or within the processing device 702 while being executed by the computer system 700; thus, in some embodiments, the volatile memory 704 and the processing device 702 also constitute machine-readable storage media.

[0140] Although the computer-readable storage medium 724 is shown as a single medium in the illustrative example, the term "computer-readable storage medium" includes a single medium or multiple media (e.g., centralized or distributed databases and / or associated caches and servers, etc.) that store one or more sets of executable instructions. The term "computer-readable storage medium" also includes tangible media that store or encode a set of instructions for execution by a computer to cause the computer to perform one or more of the methodologies described herein. The term "computer-readable storage medium" includes, but is not limited to, solid-state memory, optical media, magnetic media, etc.

[0141] In some embodiments, the methods, components, and features described herein are implemented by discrete hardware components or are integrated into the functionality of other hardware components, such as ASICS, FPGAs, DSPs, or similar devices. In some embodiments, the methods, components, and features are performed by firmware modules or functional circuitry within a hardware device. Furthermore, the methods, components, and features are performed by any combination of hardware devices and computer program components, or computer programs.

[0142] Unless otherwise specified, terms such as "receive," "cause," "provide," "train," "determine," and the like refer to actions and processes performed or implemented by a computer system that manipulate and transform data represented as physical (electronic) quantities in computer system registers and memory into other data similarly represented as physical quantities in computer system memory or registers, or other information storage, transmission, or display devices. Also, terms such as "first," "second," "third," "fourth," and the like, as used herein, are intended as labels to distinguish different elements and do not imply any ordering by numerical designation.

[0143] Examples described herein also relate to apparatus for performing the methods described herein. In some embodiments, this apparatus is specially constructed to perform the methods described herein, or comprises a general-purpose computer system selectively programmed by a computer program stored on the computer system. In some embodiments, such a computer program is stored on a computer-readable tangible storage medium.

[0144] The methods and examples described herein are not inherently related to any particular computer or other apparatus. Various general-purpose systems may be used with the teachings described herein, or more specialized apparatus may be constructed to perform the methods described herein and / or their individual functions, routines, subroutines, or operations. Examples of structures for these various systems are set forth in the description above.

[0145] The foregoing description sets forth numerous specific details, including examples of particular systems, components, methods, etc., to provide a thorough understanding of some embodiments of the present disclosure. However, it will be apparent to one skilled in the art that at least some embodiments of the present disclosure may be practiced without these specific details. In other instances, well-known components or methods have not been described in detail or have been shown in simple block diagram form in order to avoid unnecessarily obscuring the present disclosure. Thus, the specific details described are merely examples. A particular implementation may vary from these example details and still be considered within the scope of the present disclosure.

[0146] References throughout this specification to an "embodiment" or "one embodiment" mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in at least one embodiment. Thus, the appearances of the phrase "in an embodiment" or "in one embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the term "or" means an inclusive "or" rather than an exclusive "or." When the term "about" or "approximately" is used herein, it means that the stated nominal value is accurate to within ±10%.

[0147] Although the operations of the methods herein are shown and described in a particular order, the order of the operations of each method may be changed such that certain operations are performed in the reverse order, and certain operations may be performed at least in part concurrently with other operations. In other embodiments, instructions or sub-operations of separate operations are performed intermittently and / or interleaved.

[0148] It is understood that the above description is intended to be illustrative, and not limiting. Many other embodiments will become apparent to those skilled in the art upon reading and understanding the above description. Accordingly, the scope of the disclosure should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

1. 1. An enclosure system comprising: a plurality of walls forming an interior volume, the enclosure system being configured to couple to an equipment front end module (EFEM) of a substrate processing system; a charging assembly having a first charging coil, the first charging coil coupled to a lower surface of the top wall of the enclosure system; an enclosure system having one or more first support structures disposed within the interior volume below the first charging coil, the first support structures configured to support the first verification wafer within a threshold distance of the first charging coil and charge the first verification wafer via the charging assembly, the threshold distance allowing the first verification wafer to be removed from the enclosure system without contacting the first charging coil.

2. 10. The enclosure system of claim 1, wherein the one or more first support structures are configured to position the first verification wafer to align a first charging interface of the first verification wafer with the first charging coil and charge the first verification wafer via the charging assembly.

3. 10. The enclosure system of claim 1, wherein the charging assembly comprises a rechargeable battery coupled to an upper wall of the plurality of walls of the enclosure system and configured to charge the first verification wafer via a first charging coil, the rechargeable battery configured to be recharged while coupled to the enclosure system.

4. the charging assembly includes a second charging coil disposed below the one or more first support structures; 10. The enclosure system of claim 1, further comprising: one or more second support structures disposed within the interior volume below the second charging coil; the one or more second support structures configured to support the second verification wafer within a threshold distance of the second charging coil; and the one or more second support structures configured to position the second verification wafer to align a second charging interface of the second verification wafer with the second charging coil and charge the second verification wafer via the charging assembly.

5. 3. The enclosure system of claim 2, wherein the charging assembly is configured to supply electrical energy to a first charging interface of the first verification wafer in response to the first verification wafer being positioned within a threshold distance to a first charging coil of the charging assembly.

6. 10. The enclosure system of claim 1, further comprising: one or more second support structures configured to support a process kit ring within the interior volume, the one or more second support structures disposed below the one or more first support structures.

7. 4. The enclosure system of claim 3, wherein the charging assembly comprises a processor, the processor configured to receive battery data related to a state of charge of the rechargeable battery and cause corrective action related to the battery data to be taken.

8. 1. A charging assembly for an enclosure system configured to couple to an equipment front end module (EFEM) of a substrate processing system, comprising: a first charging coil configured to be disposed within the interior volume of the enclosure system above one or more first support structures that support a first verification wafer within a threshold distance of the first charging coil, the first verification wafer being positioned by the one or more first support structures to align a first charging interface of the first verification wafer with the first charging coil, the first charging coil being coupled to a lower surface of the top wall of the enclosure system, the threshold distance allowing the first verification wafer to be removed from the enclosure system without the first verification wafer contacting the first charging coil; A charging assembly comprising: a rechargeable battery configured to charge the first verification wafer via the first charging coil, the rechargeable battery configured to be recharged while coupled to the enclosure system.

9. 9. The charging assembly of claim 8, wherein the charging assembly comprises a removable lid of the enclosure system, the removable lid configured to be removably attached to a side wall of the enclosure system, and the rechargeable battery and the first charging coil coupled to the removable lid.

10. 9. The charging assembly of claim 8, wherein the charging assembly is configured to supply electrical energy to a first charging interface of the first verification wafer in response to the first verification wafer being positioned within a threshold distance to a first charging coil of the charging assembly.

11. 10. The charging assembly of claim 8, further comprising: a second charging coil configured to be positioned below the one or more first support structures of the enclosure system, wherein the rechargeable battery is configured to charge the second verification wafer via the second charging coil.

12. 12. The charging assembly of claim 11, wherein the charging assembly is configured to supply electrical energy to a second charging interface of the second verification wafer in response to the second verification wafer being positioned within a threshold distance to a second charging coil of the charging assembly, the second verification wafer being positioned by one or more second support structures to align the second charging interface of the second verification wafer with the second charging coil.

13. 9. The charging assembly of claim 8, comprising a processor configured to receive battery data related to a state of charge of a rechargeable battery and to cause corrective action related to the battery data to be performed.

14. receiving a first subset of sensor data from a verification wafer configured to be transferred by a robot of an equipment front end module (EFEM) of the substrate processing system from one or more support structures disposed within an interior volume formed by the enclosure system, the first subset being associated with a charge state of at least one electrical storage device of the verification wafer; receiving a second subset of sensor data from a charging assembly of the enclosure system, the charging assembly charging the verification wafer in response to the verification wafer being placed on the one or more support structures; A method comprising: performing corrective action associated with a substrate processing system based on sensor data.

15. Execution of the corrective action is based on the first subset of sensor data, the corrective action being: providing notice; transporting the verification wafer into the enclosure system and charging it; Performing maintenance or replacement of the verification wafer; or 15. The method of claim 14, comprising one or more of: replacing a process kit ring disposed within a processing chamber of a substrate processing system.

16. Execution of the corrective action is based on a second subset of the sensor data, the corrective action being: Providing notice. placing the enclosure system in a charging position for a predetermined period of time to at least partially charge the battery of the charging assembly; performing maintenance or replacement of at least a portion of the enclosure system; or 15. The method of claim 14, further comprising one or more of: transporting the enclosure system to a predetermined location.

17. receiving historical sensor data associated with one or more past validation wafers or one or more past enclosure systems; receiving historical performance data associated with the historical sensor data; 15. The method of claim 14, comprising training a machine learning model using data inputs including historical sensor data and target output data including historical performance data to generate a trained machine learning model configured to output predictive data for performing corrective action based on the sensor data.

18. providing the sensor data as input to a trained machine learning model; receiving prediction data as output from the trained machine learning model; The method of claim 14 , including determining corrective action based on the predictive data.

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